Identification of surface water - groundwater nitrate governing factors in Jianghuai hilly area based on coupled SWAT-MODFLOW-RT3D modeling approach,Science of the Total Environment

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Identification of surface water - groundwater nitrate governing factors in Jianghuai hilly area based on coupled SWAT-MODFLOW-RT3D modeling approach
Science of the Total Environment ( IF 8.2 ) Pub Date : 2023-11-28 , DOI: 10.1016/j.scitotenv.2023.168830
Lu Zhang ₁ , Xue Li ₂ , Jiangbo Han ₂ , Jin Lin ₂ , Yunfeng Dai ₂ , Peng Liu ₂

Affiliation

A comprehensive understanding of the key controlling factors on NO3-N spatiotemporal distribution in surface and groundwater is of great significance to nitrogen pollution control and water resources management in watershed. Hence, the coupled SWAT-MODFLOW-RT3D model was employed to simulate nitrate (NO3−) fate and transport in Huashan watershed system. The model was calibrated using a combination of stream discharge, groundwater levels, NO3-N in-stream loading and groundwater NO3-N concentrations. The simulation revealed the significant spatiotemporal variations in surface water-groundwater nitrate interactions. The annual average percolation of NO3− from rivers to groundwater was 171.5 kg/km2 and the annual average discharge NO3− content from groundwater into rivers was 451.9 kg/km2 over the simulation period. The highest percolation of NO3− from rivers to groundwater occurred in April and the highest discharge NO3− content from groundwater into rivers occurred in July. Grassland and agriculture land contributed more nitrate contents in river water and groundwater compared to bare land and forest in the study area and the water exchange was the primary driving force for nitrate interactions in the surface water-groundwater system. Sensitivity analysis indicated that river runoff and groundwater levels were most influenced by the SCS runoff curve number f (CN2) and aquifer hydraulic conductivity (K), which, in turn, significantly affected nitrate transport. Regarding water quality parameters, the denitrification exponential rate coefficient (CDN) had the most pronounced impact on NO3-N in-stream loading and groundwater NO3-N concentrations. This study underscores the central role of surface-groundwater (SW-GW) interactions in watershed-scale nitrate research and suggests that parameters with higher sensitivity should be prioritized in analogous watershed modeling.

中文翻译：

基于SWAT-MODFLOW-RT3D耦合建模方法识别江淮丘陵区地表水-地下水硝酸盐控制因子

全面认识地表水和地下水NO3-N时空分布的关键控制因素对于流域氮污染控制和水资源管理具有重要意义。因此，采用耦合的 SWAT-MODFLOW-RT3D 模型来模拟华山流域系统中硝酸盐 (NO3−) 的归宿和迁移。该模型结合河流流量、地下水位、河流内 NO3-N 负荷和地下水 NO3-N 浓度进行校准。模拟揭示了地表水-地下水硝酸盐相互作用的显着时空变化。模拟期间河流向地下水年平均渗滤NO3−为171.5 kg/km2，地下水向河流年平均排放NO3−含量为451.9 kg/km2。 NO3−从河流渗入地下水的最高值出现在4月份，而从地下水流入河流的NO3−含量最高出现在7月份。与研究区的裸地和森林相比，草地和农业用地对河水和地下水贡献了更多的硝酸盐含量，水交换是地表水-地下水系统硝酸盐相互作用的主要驱动力。敏感性分析表明，河流径流和地下水位受南海径流曲线数f（CN2）和含水层导水率（K）的影响最大，进而显着影响硝酸盐输送。在水质参数方面，反硝化指数率系数（CDN）对河流中NO3-N负荷和地下水NO3-N浓度的影响最为显着。这项研究强调了地表水-地下水（SW-GW）相互作用在流域规模硝酸盐研究中的核心作用，并建议在类似的流域建模中应优先考虑具有较高敏感性的参数。

更新日期：2023-11-28

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